Overview

Dataset statistics

Number of variables14
Number of observations10443
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory120.0 B

Variable types

Numeric14

Alerts

CALI is highly overall correlated with DT and 1 other fieldsHigh correlation
DEPT is highly overall correlated with DT and 2 other fieldsHigh correlation
DT is highly overall correlated with CALI and 3 other fieldsHigh correlation
FTEMP is highly overall correlated with DEPT and 2 other fieldsHigh correlation
GR is highly overall correlated with NPHI and 7 other fieldsHigh correlation
NPHI is highly overall correlated with CALI and 3 other fieldsHigh correlation
PERM_ATAGA is highly overall correlated with GR and 6 other fieldsHigh correlation
PERM_EFF_ATAGA is highly overall correlated with GR and 6 other fieldsHigh correlation
PHID_ATAGA is highly overall correlated with GR and 6 other fieldsHigh correlation
PHIE_ATAGA is highly overall correlated with GR and 6 other fieldsHigh correlation
RHOB is highly overall correlated with GR and 6 other fieldsHigh correlation
SP is highly overall correlated with DEPT and 8 other fieldsHigh correlation
VSH is highly overall correlated with GR and 7 other fieldsHigh correlation
DEPT has unique valuesUnique
FTEMP has unique valuesUnique

Reproduction

Analysis started2024-06-17 16:28:12.283721
Analysis finished2024-06-17 16:29:15.099043
Duration1 minute and 2.82 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

DEPT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10443
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11085.183
Minimum8201
Maximum13943.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:15.336443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8201
5-th percentile8495.05
Q19641.5
median11080.5
Q312529.25
95-th percentile13667.45
Maximum13943.5
Range5742.5
Interquartile range (IQR)2887.75

Descriptive statistics

Standard deviation1666.1419
Coefficient of variation (CV)0.15030351
Kurtosis-1.2091073
Mean11085.183
Median Absolute Deviation (MAD)1444.5
Skewness0.00012008377
Sum1.1576257 × 108
Variance2776028.8
MonotonicityStrictly increasing
2024-06-17T17:29:15.773591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8201 1
 
< 0.1%
12060.5 1
 
< 0.1%
12049 1
 
< 0.1%
12049.5 1
 
< 0.1%
12050.5 1
 
< 0.1%
12051 1
 
< 0.1%
12051.5 1
 
< 0.1%
12052.5 1
 
< 0.1%
12053 1
 
< 0.1%
12053.5 1
 
< 0.1%
Other values (10433) 10433
99.9%
ValueCountFrequency (%)
8201 1
< 0.1%
8201.5 1
< 0.1%
8202 1
< 0.1%
8202.5 1
< 0.1%
8203 1
< 0.1%
8203.5 1
< 0.1%
8204 1
< 0.1%
8204.5 1
< 0.1%
8205 1
< 0.1%
8205.5 1
< 0.1%
ValueCountFrequency (%)
13943.5 1
< 0.1%
13943 1
< 0.1%
13942.5 1
< 0.1%
13942 1
< 0.1%
13941.5 1
< 0.1%
13941 1
< 0.1%
13940.5 1
< 0.1%
13940 1
< 0.1%
13939.5 1
< 0.1%
13939 1
< 0.1%

CALI
Real number (ℝ)

HIGH CORRELATION 

Distinct4956
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.854833
Minimum8.1718998
Maximum21.686399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:16.176000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.1718998
5-th percentile8.2578001
Q111.5625
median11.8281
Q312.6939
95-th percentile15.00709
Maximum21.686399
Range13.5145
Interquartile range (IQR)1.1313996

Descriptive statistics

Standard deviation1.965782
Coefficient of variation (CV)0.16582115
Kurtosis1.2037043
Mean11.854833
Median Absolute Deviation (MAD)0.6953001
Skewness0.25334998
Sum123800.02
Variance3.8642988
MonotonicityNot monotonic
2024-06-17T17:29:16.671234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.73439884 732
 
7.0%
11.64840126 717
 
6.9%
11.5625 641
 
6.1%
8.257800102 487
 
4.7%
12.08590031 326
 
3.1%
12.1718998 287
 
2.7%
11.8281002 208
 
2.0%
12.25779915 204
 
2.0%
11.91410065 175
 
1.7%
8.343799591 130
 
1.2%
Other values (4946) 6536
62.6%
ValueCountFrequency (%)
8.171899795 27
0.3%
8.172400474 1
 
< 0.1%
8.17539978 1
 
< 0.1%
8.176600456 1
 
< 0.1%
8.184399605 1
 
< 0.1%
8.200300217 1
 
< 0.1%
8.203300476 1
 
< 0.1%
8.230600357 1
 
< 0.1%
8.252900124 1
 
< 0.1%
8.254199982 1
 
< 0.1%
ValueCountFrequency (%)
21.68639946 1
< 0.1%
21.65460014 1
< 0.1%
21.5128994 1
< 0.1%
21.38220024 1
< 0.1%
21.23049927 1
< 0.1%
21.16659927 1
< 0.1%
21.13350105 1
< 0.1%
21.06189919 1
< 0.1%
21.03409958 1
< 0.1%
20.89430046 1
< 0.1%

DT
Real number (ℝ)

HIGH CORRELATION 

Distinct4267
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.099834
Minimum50
Maximum113.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:17.075802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile75.686472
Q181.900002
median89.5
Q396
95-th percentile102.39997
Maximum113.7
Range63.699997
Interquartile range (IQR)14.099998

Descriptive statistics

Standard deviation8.6781936
Coefficient of variation (CV)0.097398538
Kurtosis-0.39710665
Mean89.099834
Median Absolute Deviation (MAD)6.9000092
Skewness-0.15347093
Sum930469.56
Variance75.311043
MonotonicityNot monotonic
2024-06-17T17:29:17.569559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.90000153 61
 
0.6%
96.40000916 52
 
0.5%
96.59999847 51
 
0.5%
97.19999695 51
 
0.5%
97.99999237 51
 
0.5%
95.49999237 50
 
0.5%
96.80000305 48
 
0.5%
97.80000305 48
 
0.5%
98.19999695 47
 
0.5%
98.80000305 47
 
0.5%
Other values (4257) 9937
95.2%
ValueCountFrequency (%)
50 1
< 0.1%
50.90000153 1
< 0.1%
52.14960098 1
< 0.1%
53.40000153 1
< 0.1%
53.49290085 1
< 0.1%
53.59999847 1
< 0.1%
54.93740082 1
< 0.1%
55.83939743 1
< 0.1%
56.09999847 1
< 0.1%
56.20000076 2
< 0.1%
ValueCountFrequency (%)
113.6999969 1
< 0.1%
113.0999985 1
< 0.1%
112.9999924 1
< 0.1%
112.4000015 1
< 0.1%
112.3000031 1
< 0.1%
112.0999985 1
< 0.1%
112 1
< 0.1%
111.5999985 1
< 0.1%
111.4997025 1
< 0.1%
111.4000092 1
< 0.1%

FTEMP
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10443
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.36291
Minimum74.98994
Maximum127.4994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:18.004101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74.98994
5-th percentile77.678737
Q188.16187
median101.3201
Q3114.56745
95-th percentile124.97514
Maximum127.4994
Range52.50946
Interquartile range (IQR)26.40558

Descriptive statistics

Standard deviation15.235201
Coefficient of variation (CV)0.15030351
Kurtosis-1.2091074
Mean101.36291
Median Absolute Deviation (MAD)13.20852
Skewness0.00012010532
Sum1058532.9
Variance232.11136
MonotonicityStrictly increasing
2024-06-17T17:29:18.441175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.98994 1
 
< 0.1%
110.2812 1
 
< 0.1%
110.1761 1
 
< 0.1%
110.1806 1
 
< 0.1%
110.1898 1
 
< 0.1%
110.1943 1
 
< 0.1%
110.1989 1
 
< 0.1%
110.2081 1
 
< 0.1%
110.2126 1
 
< 0.1%
110.2172 1
 
< 0.1%
Other values (10433) 10433
99.9%
ValueCountFrequency (%)
74.98994 1
< 0.1%
74.99451 1
< 0.1%
74.99908 1
< 0.1%
75.00366 1
< 0.1%
75.00823 1
< 0.1%
75.0128 1
< 0.1%
75.01737 1
< 0.1%
75.02195 1
< 0.1%
75.02652 1
< 0.1%
75.03109 1
< 0.1%
ValueCountFrequency (%)
127.4994 1
< 0.1%
127.4948 1
< 0.1%
127.4902 1
< 0.1%
127.4856 1
< 0.1%
127.4811 1
< 0.1%
127.4765 1
< 0.1%
127.4719 1
< 0.1%
127.4674 1
< 0.1%
127.4628 1
< 0.1%
127.4582 1
< 0.1%

GR
Real number (ℝ)

HIGH CORRELATION 

Distinct6167
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.440398
Minimum14.9364
Maximum143.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:18.853702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.9364
5-th percentile22.48512
Q136
median77
Q389.4063
95-th percentile101.78033
Maximum143.25
Range128.3136
Interquartile range (IQR)53.4063

Descriptive statistics

Standard deviation28.491466
Coefficient of variation (CV)0.43538039
Kurtosis-1.4221657
Mean65.440398
Median Absolute Deviation (MAD)20.625
Skewness-0.22603653
Sum683394.07
Variance811.76363
MonotonicityNot monotonic
2024-06-17T17:29:19.354837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.625 27
 
0.3%
84.375 20
 
0.2%
87 20
 
0.2%
83.5625 19
 
0.2%
85.875 19
 
0.2%
87.625 18
 
0.2%
87.6875 18
 
0.2%
88.625 18
 
0.2%
87.5 17
 
0.2%
86.1875 17
 
0.2%
Other values (6157) 10250
98.2%
ValueCountFrequency (%)
14.93640041 1
< 0.1%
15.12279987 1
< 0.1%
15.47290039 1
< 0.1%
15.94089985 1
< 0.1%
16.06049919 1
< 0.1%
16.11120033 1
< 0.1%
16.18840027 1
< 0.1%
16.25180054 1
< 0.1%
16.27700043 1
< 0.1%
16.30270004 1
< 0.1%
ValueCountFrequency (%)
143.25 1
< 0.1%
141.75 1
< 0.1%
135 1
< 0.1%
133 1
< 0.1%
129.3813934 1
< 0.1%
127.6875 1
< 0.1%
127.6406021 1
< 0.1%
127.5 1
< 0.1%
127 1
< 0.1%
126.125 1
< 0.1%

ILD
Real number (ℝ)

Distinct5311
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7229505
Minimum1.2725
Maximum318.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:19.871414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2725
5-th percentile1.4648
Q11.79295
median2.3828001
Q33.1289001
95-th percentile5.49922
Maximum318.25
Range316.9775
Interquartile range (IQR)1.3359501

Descriptive statistics

Standard deviation17.792438
Coefficient of variation (CV)3.7672293
Kurtosis138.50577
Mean4.7229505
Median Absolute Deviation (MAD)0.64059997
Skewness11.051925
Sum49321.772
Variance316.57083
MonotonicityNot monotonic
2024-06-17T17:29:20.385797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.467800021 16
 
0.2%
2.511699915 15
 
0.1%
2.355499983 15
 
0.1%
2.398400068 15
 
0.1%
1.515599966 13
 
0.1%
2.372999907 13
 
0.1%
2.267600059 13
 
0.1%
2.611299992 13
 
0.1%
2.183599949 13
 
0.1%
2.513700008 13
 
0.1%
Other values (5301) 10304
98.7%
ValueCountFrequency (%)
1.272500038 1
< 0.1%
1.273399949 1
< 0.1%
1.274399996 1
< 0.1%
1.275400043 1
< 0.1%
1.278300047 1
< 0.1%
1.279299974 1
< 0.1%
1.284199953 1
< 0.1%
1.285300016 1
< 0.1%
1.28610003 1
< 0.1%
1.288599968 1
< 0.1%
ValueCountFrequency (%)
318.25 1
< 0.1%
310.5 1
< 0.1%
291.5007935 1
< 0.1%
289.25 1
< 0.1%
281.25 1
< 0.1%
275.5 1
< 0.1%
275 1
< 0.1%
274.75 1
< 0.1%
274 1
< 0.1%
267.7502136 1
< 0.1%

NPHI
Real number (ℝ)

HIGH CORRELATION 

Distinct9832
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.191539
Minimum3.5532999
Maximum57.134998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:20.763731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.5532999
5-th percentile16.09095
Q121.9794
median28.0121
Q336.249901
95-th percentile45.668681
Maximum57.134998
Range53.581698
Interquartile range (IQR)14.270501

Descriptive statistics

Standard deviation9.298245
Coefficient of variation (CV)0.31852535
Kurtosis-0.67544387
Mean29.191539
Median Absolute Deviation (MAD)6.7383003
Skewness0.37256649
Sum304847.24
Variance86.45736
MonotonicityNot monotonic
2024-06-17T17:29:21.217996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.24069977 4
 
< 0.1%
24.44459915 4
 
< 0.1%
28.51259995 4
 
< 0.1%
31.65279961 4
 
< 0.1%
22.6317997 4
 
< 0.1%
27.28580093 3
 
< 0.1%
30.15749931 3
 
< 0.1%
43.28609848 3
 
< 0.1%
31.6284008 3
 
< 0.1%
34.65269852 3
 
< 0.1%
Other values (9822) 10408
99.7%
ValueCountFrequency (%)
3.553299904 1
< 0.1%
3.662100077 1
< 0.1%
3.941299915 1
< 0.1%
4.513500214 1
< 0.1%
4.565100193 1
< 0.1%
4.653900146 1
< 0.1%
5.209400177 1
< 0.1%
6.058100224 1
< 0.1%
6.591800213 1
< 0.1%
7.230500221 1
< 0.1%
ValueCountFrequency (%)
57.13499832 1
< 0.1%
57.10449982 1
< 0.1%
56.72600174 1
< 0.1%
56.28659821 1
< 0.1%
56.13359833 1
< 0.1%
55.87459946 1
< 0.1%
55.54729843 1
< 0.1%
55.31010055 1
< 0.1%
54.74240112 1
< 0.1%
54.53409958 1
< 0.1%

PERM_ATAGA
Real number (ℝ)

HIGH CORRELATION 

Distinct3546
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3986.6598
Minimum7.64001 × 10-5
Maximum199670.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:21.626274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.64001 × 10-5
5-th percentile17.368206
Q1201.38622
median1220.9786
Q34585.4575
95-th percentile15370.483
Maximum199670.89
Range199670.89
Interquartile range (IQR)4384.0713

Descriptive statistics

Standard deviation9980.9473
Coefficient of variation (CV)2.5035864
Kurtosis180.42344
Mean3986.6598
Median Absolute Deviation (MAD)1180.7616
Skewness11.445597
Sum41632688
Variance99619309
MonotonicityNot monotonic
2024-06-17T17:29:22.133840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4835.108398 13
 
0.1%
743.6452637 13
 
0.1%
3613.582275 11
 
0.1%
4395.577148 11
 
0.1%
3055.088867 11
 
0.1%
3866.69165 11
 
0.1%
3852.230225 11
 
0.1%
4653.176758 11
 
0.1%
3174.887451 10
 
0.1%
4307.226562 10
 
0.1%
Other values (3536) 10331
98.9%
ValueCountFrequency (%)
7.64001 × 10-51
< 0.1%
0.0001536546 1
< 0.1%
0.003118847 1
< 0.1%
0.0087134587 1
< 0.1%
0.0420583598 1
< 0.1%
0.0895343572 1
< 0.1%
0.1166751236 1
< 0.1%
0.1235404611 1
< 0.1%
0.1711667031 2
< 0.1%
0.1732272059 1
< 0.1%
ValueCountFrequency (%)
199670.8906 1
< 0.1%
197689.8594 1
< 0.1%
196708.2812 1
< 0.1%
195728.375 1
< 0.1%
193783.125 1
< 0.1%
191854.0938 1
< 0.1%
189937.9688 1
< 0.1%
180147.3125 1
< 0.1%
177578.4062 1
< 0.1%
171217.3906 1
< 0.1%

PERM_EFF_ATAGA
Real number (ℝ)

HIGH CORRELATION 

Distinct3546
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3986.6598
Minimum7.64001 × 10-5
Maximum199670.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:22.699106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.64001 × 10-5
5-th percentile17.368206
Q1201.38622
median1220.9786
Q34585.4575
95-th percentile15370.483
Maximum199670.89
Range199670.89
Interquartile range (IQR)4384.0713

Descriptive statistics

Standard deviation9980.9473
Coefficient of variation (CV)2.5035864
Kurtosis180.42344
Mean3986.6598
Median Absolute Deviation (MAD)1180.7616
Skewness11.445597
Sum41632688
Variance99619309
MonotonicityNot monotonic
2024-06-17T17:29:23.166611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4835.108398 13
 
0.1%
743.6452637 13
 
0.1%
3613.582275 11
 
0.1%
4395.577148 11
 
0.1%
3055.088867 11
 
0.1%
3866.69165 11
 
0.1%
3852.230225 11
 
0.1%
4653.176758 11
 
0.1%
3174.887451 10
 
0.1%
4307.226562 10
 
0.1%
Other values (3536) 10331
98.9%
ValueCountFrequency (%)
7.64001 × 10-51
< 0.1%
0.0001536546 1
< 0.1%
0.003118847 1
< 0.1%
0.0087134587 1
< 0.1%
0.0420583598 1
< 0.1%
0.0895343572 1
< 0.1%
0.1166751236 1
< 0.1%
0.1235404611 1
< 0.1%
0.1711667031 2
< 0.1%
0.1732272059 1
< 0.1%
ValueCountFrequency (%)
199670.8906 1
< 0.1%
197689.8594 1
< 0.1%
196708.2812 1
< 0.1%
195728.375 1
< 0.1%
193783.125 1
< 0.1%
191854.0938 1
< 0.1%
189937.9688 1
< 0.1%
180147.3125 1
< 0.1%
177578.4062 1
< 0.1%
171217.3906 1
< 0.1%

PHID_ATAGA
Real number (ℝ)

HIGH CORRELATION 

Distinct3546
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22603167
Minimum-0.016787905
Maximum0.43842426
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)< 0.1%
Memory size163.2 KiB
2024-06-17T17:29:23.642428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.016787905
5-th percentile0.13115154
Q10.18354548
median0.22896963
Q30.26933333
95-th percentile0.31242421
Maximum0.43842426
Range0.45521216
Interquartile range (IQR)0.085787855

Descriptive statistics

Standard deviation0.056953606
Coefficient of variation (CV)0.2519718
Kurtosis-0.34467496
Mean0.22603167
Median Absolute Deviation (MAD)0.042363644
Skewness-0.11269147
Sum2360.4487
Variance0.0032437133
MonotonicityNot monotonic
2024-06-17T17:29:24.037672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2710909843 13
 
0.1%
0.2154544741 13
 
0.1%
0.2615757585 11
 
0.1%
0.2679393589 11
 
0.1%
0.2562423944 11
 
0.1%
0.2637576461 11
 
0.1%
0.2636364102 11
 
0.1%
0.2698182464 11
 
0.1%
0.2574545741 10
 
0.1%
0.2672726512 10
 
0.1%
Other values (3536) 10331
98.9%
ValueCountFrequency (%)
-0.016787905 1
< 0.1%
0.0188613087 1
< 0.1%
0.0311515685 1
< 0.1%
0.0369697064 1
< 0.1%
0.0480606481 1
< 0.1%
0.0545103773 1
< 0.1%
0.0569697022 1
< 0.1%
0.0575151742 1
< 0.1%
0.0607273206 2
< 0.1%
0.0608485527 1
< 0.1%
ValueCountFrequency (%)
0.4384242594 1
< 0.1%
0.4376962781 1
< 0.1%
0.4373333156 1
< 0.1%
0.4369694591 1
< 0.1%
0.43624264 1
< 0.1%
0.4355158508 1
< 0.1%
0.4347878695 1
< 0.1%
0.4309697151 1
< 0.1%
0.4299392998 1
< 0.1%
0.4273333251 1
< 0.1%

PHIE_ATAGA
Real number (ℝ)

HIGH CORRELATION 

Distinct10378
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1877014
Minimum0.031235384
Maximum0.37015748
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:24.577863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.031235384
5-th percentile0.097260157
Q10.13064526
median0.17889935
Q30.24727331
95-th percentile0.28707885
Maximum0.37015748
Range0.3389221
Interquartile range (IQR)0.11662805

Descriptive statistics

Standard deviation0.064453147
Coefficient of variation (CV)0.34338129
Kurtosis-1.2645018
Mean0.1877014
Median Absolute Deviation (MAD)0.058202751
Skewness0.11774254
Sum1960.1657
Variance0.0041542081
MonotonicityNot monotonic
2024-06-17T17:29:24.994727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1034147516 5
 
< 0.1%
0.1060342714 4
 
< 0.1%
0.105112344 3
 
< 0.1%
0.1029665023 3
 
< 0.1%
0.1075379923 3
 
< 0.1%
0.1038596407 3
 
< 0.1%
0.100069873 3
 
< 0.1%
0.0989819244 3
 
< 0.1%
0.1006736159 3
 
< 0.1%
0.1070612147 3
 
< 0.1%
Other values (10368) 10410
99.7%
ValueCountFrequency (%)
0.0312353838 1
< 0.1%
0.0377725959 1
< 0.1%
0.0525283031 1
< 0.1%
0.0560884178 1
< 0.1%
0.0579369254 1
< 0.1%
0.058584366 1
< 0.1%
0.0589860789 1
< 0.1%
0.0590879805 1
< 0.1%
0.0611286424 1
< 0.1%
0.0612098984 1
< 0.1%
ValueCountFrequency (%)
0.3701574802 1
< 0.1%
0.366309464 1
< 0.1%
0.3652623296 1
< 0.1%
0.3587108254 1
< 0.1%
0.3493294418 1
< 0.1%
0.3464449644 1
< 0.1%
0.341789633 1
< 0.1%
0.340634495 1
< 0.1%
0.3365918696 1
< 0.1%
0.3352850676 1
< 0.1%

RHOB
Real number (ℝ)

HIGH CORRELATION 

Distinct3546
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2770478
Minimum1.9266
Maximum2.6777
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:25.427735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9266
5-th percentile2.1345
Q12.2056
median2.2722001
Q32.34715
95-th percentile2.4335999
Maximum2.6777
Range0.75110006
Interquartile range (IQR)0.14154994

Descriptive statistics

Standard deviation0.09397345
Coefficient of variation (CV)0.041269864
Kurtosis-0.34467494
Mean2.2770478
Median Absolute Deviation (MAD)0.069900036
Skewness0.11269147
Sum23779.21
Variance0.0088310093
MonotonicityNot monotonic
2024-06-17T17:29:25.924491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.2026999 13
 
0.1%
2.294500113 13
 
0.1%
2.218400002 11
 
0.1%
2.207900047 11
 
0.1%
2.227200031 11
 
0.1%
2.214799881 11
 
0.1%
2.214999914 11
 
0.1%
2.20479989 11
 
0.1%
2.225199938 10
 
0.1%
2.209000111 10
 
0.1%
Other values (3536) 10331
98.9%
ValueCountFrequency (%)
1.926599979 1
< 0.1%
1.927801132 1
< 0.1%
1.92840004 1
< 0.1%
1.929000378 1
< 0.1%
1.930199623 1
< 0.1%
1.931398869 1
< 0.1%
1.932600021 1
< 0.1%
1.938899994 1
< 0.1%
1.940600157 1
< 0.1%
1.944900036 1
< 0.1%
ValueCountFrequency (%)
2.677700043 1
< 0.1%
2.618878841 1
< 0.1%
2.598599911 1
< 0.1%
2.588999987 1
< 0.1%
2.57069993 1
< 0.1%
2.560057878 1
< 0.1%
2.555999994 1
< 0.1%
2.555099964 1
< 0.1%
2.549799919 2
< 0.1%
2.549599886 1
< 0.1%

SP
Real number (ℝ)

HIGH CORRELATION 

Distinct3322
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.631568
Minimum-1.5
Maximum127.3022
Zeros10
Zeros (%)0.1%
Negative27
Negative (%)0.3%
Memory size163.2 KiB
2024-06-17T17:29:26.394424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.5
5-th percentile14
Q120.5
median55.291
Q380.8078
95-th percentile119.81561
Maximum127.3022
Range128.8022
Interquartile range (IQR)60.3078

Descriptive statistics

Standard deviation34.0339
Coefficient of variation (CV)0.61177316
Kurtosis-0.96417069
Mean55.631568
Median Absolute Deviation (MAD)28.209
Skewness0.33207097
Sum580960.47
Variance1158.3064
MonotonicityNot monotonic
2024-06-17T17:29:27.320015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 216
 
2.1%
17.5 205
 
2.0%
19 186
 
1.8%
18.5 181
 
1.7%
17 167
 
1.6%
81.5 165
 
1.6%
19.5 157
 
1.5%
81 156
 
1.5%
16.5 142
 
1.4%
15.5 132
 
1.3%
Other values (3312) 8736
83.7%
ValueCountFrequency (%)
-1.5 3
 
< 0.1%
-1 7
0.1%
-0.5 17
0.2%
0 10
0.1%
0.5 1
 
< 0.1%
0.5001999736 1
 
< 0.1%
1.5 3
 
< 0.1%
2 12
0.1%
2.5 13
0.1%
2.500099897 1
 
< 0.1%
ValueCountFrequency (%)
127.3022003 1
< 0.1%
127.1249924 1
< 0.1%
127.1215973 2
< 0.1%
127.0625 1
< 0.1%
127.0557022 1
< 0.1%
127.0522003 2
< 0.1%
127.0000076 1
< 0.1%
126.9897079 1
< 0.1%
126.9340973 1
< 0.1%
126.8886032 1
< 0.1%

VSH
Real number (ℝ)

HIGH CORRELATION 

Distinct6167
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.19715179
Minimum0.021398818
Maximum0.87684977
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size163.2 KiB
2024-06-17T17:29:27.763717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.021398818
5-th percentile0.035953978
Q10.067266546
median0.22230335
Q30.29534724
95-th percentile0.38560534
Maximum0.87684977
Range0.85545095
Interquartile range (IQR)0.2280807

Descriptive statistics

Standard deviation0.12636643
Coefficient of variation (CV)0.6409601
Kurtosis-0.73218813
Mean0.19715179
Median Absolute Deviation (MAD)0.11294959
Skewness0.27916989
Sum2058.8562
Variance0.015968475
MonotonicityNot monotonic
2024-06-17T17:29:28.250881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3456430733 27
 
0.3%
0.2638250887 20
 
0.2%
0.2799289823 20
 
0.2%
0.2589868605 19
 
0.2%
0.2729377151 19
 
0.2%
0.2838721871 18
 
0.2%
0.2842688262 18
 
0.2%
0.2902705967 18
 
0.2%
0.283080101 17
 
0.2%
0.2748661041 17
 
0.2%
Other values (6157) 10250
98.2%
ValueCountFrequency (%)
0.0213988181 1
< 0.1%
0.0217358246 1
< 0.1%
0.0223717429 1
< 0.1%
0.0232278462 1
< 0.1%
0.0234477408 1
< 0.1%
0.0235410966 1
< 0.1%
0.0236834027 1
< 0.1%
0.0238004141 1
< 0.1%
0.0238469578 1
< 0.1%
0.023894446 1
< 0.1%
ValueCountFrequency (%)
0.8768497705 1
< 0.1%
0.852275908 1
< 0.1%
0.7492502928 1
< 0.1%
0.7209628224 1
< 0.1%
0.6722032428 1
< 0.1%
0.6504058838 1
< 0.1%
0.6498113275 1
< 0.1%
0.6480320096 1
< 0.1%
0.6417395473 1
< 0.1%
0.6308575869 1
< 0.1%

Interactions

2024-06-17T17:29:10.039106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:13.382810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:17.634638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:21.850977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:25.924996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:29.894462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:34.277528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:38.444367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:43.544025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:47.790891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:52.446211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:56.646585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:01.054362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:05.606239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:10.303974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:13.665747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:17.905705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:22.168167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:26.200666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:30.204059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:34.546196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:38.706651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:43.833905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:48.071396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:52.824007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:57.051259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:01.764433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:05.875385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:10.596589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:13.958489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:18.188718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:22.477078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:26.465784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:30.523898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:34.943865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:40.124843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:44.135862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:48.376479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:53.194056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:57.338293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:02.113509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:06.143867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:10.990446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:14.256069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:18.472206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:22.791241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:26.767254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:30.779930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:35.310443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:40.386299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:44.419392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:48.705955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:53.509075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:57.602452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:02.440274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:06.398074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:11.420300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:14.525286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:18.744164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:23.062540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:27.014959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:31.036481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:35.562169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:40.639835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:44.742531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:49.079687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:53.877522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:57.854620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:02.751247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:06.691960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:11.694308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:14.788482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:19.075820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:23.323917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:27.321083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:31.381078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:35.848461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:40.873934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:45.034240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:49.396523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:54.141953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:58.186541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:03.033915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:07.000462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:11.943743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:15.078942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:19.412195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:23.623819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:27.619251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:31.651526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:36.104921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:41.183896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:45.364896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:49.756062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:54.395978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:58.481217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:03.329780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:07.267729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:12.173709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:15.384032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:19.693716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:23.888440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:27.859988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:32.022741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:36.404206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:41.558124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:45.704003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:50.116193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:54.672534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:58.733945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:03.576715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:07.637586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:12.466638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:15.685925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:20.036145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:24.184184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:28.257124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:32.363945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:36.767899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:41.863414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:46.061104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:50.507905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:54.999774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:59.144113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:03.878266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:07.972817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:12.767009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:15.993682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:20.353895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:24.556242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:28.536039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:32.733857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:37.057487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:42.136019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:46.354047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:50.815666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:55.280581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:59.479056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:04.204221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:08.324162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:13.010872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:16.326886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:20.600163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:24.809726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:28.784969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:33.010640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:37.320975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:42.385774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:46.650206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:51.164865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:55.513927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:59.771551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:04.461406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:08.573868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:13.279583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:16.708911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:20.906669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:25.077533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:29.056357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:33.324089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:37.595285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:42.637051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:46.929226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:51.478686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:55.781694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:00.098351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:04.739267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:08.903831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:13.598503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:17.004079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:21.223860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:25.417732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:29.338054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:33.696248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:37.886689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:43.025133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:47.244212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:51.852393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:56.119017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:00.437701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:05.086516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:09.308526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:13.862847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:17.336169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:21.528909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:25.682073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:29.633728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:34.031433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:38.197394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:43.272842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:47.523865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:52.140019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:28:56.412699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:00.787439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:05.360928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-17T17:29:09.664087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-06-17T17:29:28.528638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CALIDEPTDTFTEMPGRILDNPHIPERM_ATAGAPERM_EFF_ATAGAPHID_ATAGAPHIE_ATAGARHOBSPVSH
CALI1.000-0.4790.559-0.4790.287-0.2980.658-0.162-0.162-0.162-0.2210.1620.0290.287
DEPT-0.4791.000-0.7341.0000.1980.110-0.274-0.374-0.374-0.374-0.3470.3740.6330.198
DT0.559-0.7341.000-0.7340.119-0.4030.6930.2190.2190.2190.122-0.219-0.1720.119
FTEMP-0.4791.000-0.7341.0000.1980.110-0.274-0.374-0.374-0.374-0.3470.3740.6330.198
GR0.2870.1980.1190.1981.000-0.0110.597-0.657-0.657-0.657-0.8420.6570.6681.000
ILD-0.2980.110-0.4030.110-0.0111.000-0.450-0.128-0.128-0.128-0.0860.1280.091-0.011
NPHI0.658-0.2740.693-0.2740.597-0.4501.000-0.219-0.219-0.219-0.3710.2190.4000.597
PERM_ATAGA-0.162-0.3740.219-0.374-0.657-0.128-0.2191.0001.0001.0000.950-1.000-0.626-0.657
PERM_EFF_ATAGA-0.162-0.3740.219-0.374-0.657-0.128-0.2191.0001.0001.0000.950-1.000-0.626-0.657
PHID_ATAGA-0.162-0.3740.219-0.374-0.657-0.128-0.2191.0001.0001.0000.950-1.000-0.626-0.657
PHIE_ATAGA-0.221-0.3470.122-0.347-0.842-0.086-0.3710.9500.9500.9501.000-0.950-0.695-0.842
RHOB0.1620.374-0.2190.3740.6570.1280.219-1.000-1.000-1.000-0.9501.0000.6260.657
SP0.0290.633-0.1720.6330.6680.0910.400-0.626-0.626-0.626-0.6950.6261.0000.668
VSH0.2870.1980.1190.1981.000-0.0110.597-0.657-0.657-0.657-0.8420.6570.6681.000

Missing values

2024-06-17T17:29:14.234096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-17T17:29:14.811759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DEPTCALIDTFTEMPGRILDNPHIPERM_ATAGAPERM_EFF_ATAGAPHID_ATAGAPHIE_ATAGARHOBSPVSH
85788201.011.734398842103.9000091674.9899443.5312995911.989300012629.79509925830580.27343830580.2734380.33993947510.30996870992.08909988400.00.0881649703
85798201.511.734398842104.1999969574.9945138.1250000001.986299991630.01399993933206.87890633206.8789060.34339392190.31836384532.08340001110.00.0728902444
85808202.011.734398842104.5000000074.9990835.8125000001.981400013030.86170005837279.50390637279.5039060.34830304980.32504332072.07529997830.00.0667801797
85818202.511.734398842103.6000061075.0036636.7812995911.969699978830.68700027541492.64453141492.6445310.35290914770.32844892142.06769990920.00.0693102330
85828203.011.734398842102.5999984775.0082338.5937995911.951200008432.17010116639614.46484439614.4648440.35090902450.32488596442.07100009920.00.0741589591
85838203.511.734398842101.6999969575.0128040.6250000001.937500000033.23540115433930.24218833930.2421880.34430310130.31683585052.08189988140.00.0797764063
85848204.011.734398842100.5999984775.0173741.2500000001.935500025733.39419937129272.44921929272.4492190.33812126520.31054916982.09209990500.00.0815449581
85858204.511.734398842100.9000015375.0219541.3437995911.942399978633.11500167827686.44335927686.4433590.33581814170.30834418542.0959000587-0.50.0818120316
85868205.011.734398842101.1000061075.0265240.0937995911.947299957333.04899978627849.78906327849.7890630.33606061340.30975103382.0954999924-0.50.0782882273
85878205.511.734398842101.5000000075.0310943.3750000001.944300055531.70779991128679.13281328679.1328130.33727279310.30769294502.0934998989-0.50.0877030343
DEPTCALIDTFTEMPGRILDNPHIPERM_ATAGAPERM_EFF_ATAGAPHID_ATAGAPHIE_ATAGARHOBSPVSH
2005413939.08.463899612486.494598389127.4582107.931297301.841199994137.10390090925.830730438025.83073043800.14012114700.08427171412.4188001156121.890502930.4381886125
2005513939.58.483099937486.405502319127.4628109.269401551.854699969337.23289871214.381415367014.38141536700.12709091600.08244189622.4402999878121.032203670.4503873587
2005613940.08.506500244186.400009155127.4674110.202499391.866600036639.47529983524.136117935024.13611793500.13854540880.08114062992.4214000702120.173896790.4590624869
2005713940.58.352700233586.400009155127.4719120.118797301.880100011841.12699890120.465417862020.46541786200.13478793200.06593336162.4275999069120.750503540.5604442954
2005813941.08.365900039786.494598389127.4765119.505599981.889199972243.19169998223.946731567023.94673156700.13836362960.06695124512.4217000008119.999298100.5536583662
2005913941.58.337599754386.500000000127.4811115.950897221.904399991039.76350021449.900196075049.90019607500.15466669200.07490403212.3947999477119.088897710.5157067776
2006013942.08.350700378486.594596863127.4856111.731597901.930199980738.01699829179.480171204079.48017120400.16375753280.08620443942.3798000813118.084297180.4735848904
2006113942.58.425399780386.599998474127.4902108.781700131.950999975236.15610122774.131095886074.13109588600.16236357390.08996426312.3821001053117.079597470.4459085763
2006213943.08.437100410586.599998474127.4948112.584297181.957700014138.37139892614.924751282014.92475128200.12787885960.07772228122.4389998913116.074996950.4818514884
2006313943.58.289799690286.599998474127.4994111.866996771.952499985740.2004013067.53899335867.53899335860.11412123590.07876659932.4616999626115.510002140.4748893380